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Completed

NCT Number: NCT05218525

Testing a Prediction Algorithm Into a Running Telehealth System for Patients With COPD

This trial will test a COPD prediction algorithm into a telehealth system from the previous Danish large-scale trial, TeleCare North (NCT01984840). The COPD prediction algorithm aims to support clinical decisions by predicting exacerbations in patients with COPD based on selected physiological parameters (blood pressure, oxygen saturation, and pulse). A prospective, parallel two-armed randomized controlled trial with approximately 200 COPD participants will be conducted.

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Key information

Conditions

Chronic Obstructive Pulmonary Disease COPD COPD Exacerbation COPD Exacerbation Acute Chronic Disease Disease Attributes Lung Diseases Lung Diseases, Obstructive Pathologic Processes Pathological Conditions, Signs and Symptoms Pulmonary Disease, Chronic Obstructive Respiratory Tract Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Aalborg University

Aalborg, Denmark

About this study

Several studies call for research investigating telehealth' ability to predict exacerbations. Use of clinical prediction tools might be promising to improve telehealth services related to prediction of exacerbations and to support decision-making. However, more research is needed to further develop, test, and validate prediction algorithms to ensure that these algorithms improve clinical outcomes before they are widely implemented in practice.

This trial seeks to demonstrate that through telehealth, the implementation of a COPD prediction algorithm might have potential to support early detection of exacerbations. The COPD prediction algorithm might initiate timely treatment, which can potentially led to improvement in COPD patients' health and fewer hospitalizations. The primary outcome is the number of exacerbations defined as an all-cause acute hospitalization from baseline to follow-up in both groups. The trial hypothesizes that integrating a COPD prediction algorithm into the telehealth system will lead to a significantly lower number of exacerbations through early identification and timely preventive treatment. The primary outcome will be statistically analyzed, and the hypothesis will be tested between groups.

All participants are familiar with the telehealth system in advance. In addition to the participants' usual monitored measurements, they are asked to measure their oxygen saturation twice a week during the trial period.

The participants will receive the questionnaires; EuroQol-5D-5L, Short-Form 12 item, version 2 Health Survey, The European Health Literacy Survey Questionnaire, The Danish Test of Functional Health Literacy in Adults, Danish Telehealth Usability Questionnaire, and a questionnaire containing selected demographic characteristics at baseline and at 6-month follow-up.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

The trial population consists of patients with COPD who already use the telehealth system.

Inclusion criteria

  • Men and women >18 years
  • Diagnosis of COPD
  • Fixed residence in Aalborg Municipality.

Exclusion criteria

  • Unable to monitor vital signs
  • Unable to complete study questionnaires

Treatment and study plan

Algorithm

Other

Participants in the intervention group will receive the general offer of the telehealth intervention including the telehealth system with the implemented COPD prediction algorithm. The participants are asked to measure their vital signs and respond to COPD related questions as usual. "As usual" refers to fixed days in the week, either Monday or Thursday, where the participants must measure their vital signs. In addition, the participants must weekly measure two oxygen saturation measurements drawn from the fingertip pulse oximeter.

Primary outcomes

  1. Exacerbations

    Time frame: 6 months follow-up

    The primary outcome is the number of exacerbations defined as an all-cause acute hospitalization from baseline to follow-up in both groups. The trial hypothesizes that integrating a COPD prediction algorithm into the telehealth system will lead to a significantly lower number of exacerbations through early identification and timely preventive treatment

Secondary outcomes

  1. To compare the change in health-related quality of life (SF-12v2) at the individual level from baseline to follow-up at 6 months.

    Time frame: 6 months follow-up

    The change in health-related quality of life (HRQoL) using SF-12v2 at the individual level from baseline to follow-up at 6 months. The trial hypothesizes that the difference in HRQoL from baseline to follow-up in both groups decrease since the participants have lived six months longer with COPD. However, it is expected that the decrease in HRQoL will be lower for the intervention group compared to the control group

  2. To compare the change in health-related quality of life (EQ5D-5L) at the individual level from baseline to follow-up at 6 months.

    Time frame: 6 months follow-up

    The change in health-related quality of life (HRQoL) using EQ-5D-5L at the individual level from baseline to follow-up at 6 months. The trial hypothesizes that the difference in HRQoL from baseline to follow-up in both groups decrease since the participants have lived six months longer with COPD. However, it is expected that the decrease in HRQoL will be lower for the intervention group compared to the control group

  3. To compare the ICER (EQ-5D-5L) measured as the cost per quality adjusted life years (QALY) at the individual level from baseline to follow up at 6 months

    Time frame: 6 months follow-up

    The incremental cost-effectiveness ratio or ICER measured as the total cost per quality adjusted life years (QALY) gained for the cost-categories included in the study from baseline to follow up at six months. It is hypothesized that the cost of hospital contacts will decrease, but it is unknown whether this cost is offset by an increase in other cost-categories such as community care

Other outcomes

  1. Health literacy level

    Time frame: Baseline

    To assess the participants' health literacy level at baseline using the HLS-EU-Q16, supported by further assessment with the Danish TOFHLA during the trial period to examine whether the effect of the COPD prediction algorithm is similar in patients with COPD, regardless of health literacy level

  2. Estimation of the specialized COPD community nurse's level of participant's health literacy

    Time frame: Through study completion, an average of six months

    To examine whether the specialized COPD community nurse's estimate of the individual participant's level of health literacy influences the effect of the COPD prediction algorithm

  3. Evaluation of the specialized COPD community nurses' experiences with the usability of the COPD prediction algorithm

    Time frame: 6 months follow-up

    To evaluate the specialized COPD community nurses' experiences with the usability of the COPD prediction algorithm using interviews

  4. Evaluation of the participants experiences' with the usability of the telehealth system

    Time frame: 6 months follow-up

    To evaluate the participants' experiences with the usability of the telehealth system after trial completion using the questionnaire D-TUQ

  5. Evaluation of the participants' experience with data ethical aspects

    Time frame: 6 months follow-up

    To evaluate the participants' experiences with data ethical aspects after trial completion using qualitative research interviews

Sponsors and collaborators

Lead sponsor

Aalborg University

Other

Registry information

Official study title

Can a Predictive Algorithm Used to Flag Risk of Exacerbations in a Telehealth System Strengthen the Effectiveness and Cost-effectiveness Outcomes When Monitoring Patients With COPD?

Important dates

Study start
2021
Primary completion
2022
Study completion
2022
First posted
Feb 1, 2022
Registry last updated
Aug 15, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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